You can train custom object detectors using deep learning and machine learning algorithms
such as YOLO v2, Faster R-CNN, and ACF. For semantic segmentation you can use deep learning
algorithms such as SegNet, U-Net, and DeepLab. Pretrained models let you detect faces,
pedestrians, and other common objects.

You can accelerate your algorithms by running them on multicore processors and GPUs. Most
toolbox algorithms support C/C++ code generation for integrating with existing code, desktop
prototyping, and embedded vision system deployment.

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